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Python for Information Professionals

How to Design Practical Applications to Capitalize on the Data Explosion
Book Hero Magic crafted this summary to help describe this book. While it's new and still learning, it may not be perfect - your feedback is welcome! Summary
Python for Information Professionals introduces Python programming tailored for library and information professionals with minimal experience. It focuses on developing practical applications to retrieve, clean, and analyse large datasets, support traditional library tasks, and enhance library value. The book also addresses data security and privacy considerations relevant to data analysis using Python.
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Format: Paperback / softback
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Book Hero Magic created this recommendation. While it's new and still learning, it may not be perfect - your feedback is welcome! IS THIS YOUR NEXT READ?

Information professionals, graduate students, faculty, and professionals interested in applying Python to data science within library and information contexts.

Book Hero thinking about your next read

Python for Information Professionals: How to Design Practical Applications to Capitalize on the Data Explosion is an introduction to the Python programming language for library and information professionals with little or no prior experience.

Book Hero Magic formatted this description to make it easier to read. While it's new and still learning, it may not be perfect - your feedback is welcome! Description

Python for Information Professionals: How to Design Practical Applications to Capitalize on the Data Explosion is an introduction to the Python programming language for library and information professionals with little or no prior experience. Unlike many Python books available today that focus on the language from a general perspective, this book is specifically crafted for information professionals seeking to advance their career prospects or embrace new challenges by acquiring skills in the rapidly expanding field of data science.

Readers of Python for Information Professionals will learn to:

  • Develop Python applications for the retrieval, cleaning, and analysis of large datasets.
  • Design applications to support traditional library functions and create new opportunities to maximise library value.
  • Consider data security and privacy relevant to data analysis when using the Python language.

Book Hero Magic summarised reviews for this book. While it's new and still learning, it may not be perfect - your feedback is welcome! HOW HAS THIS BEEN REVIEWED?

Python for Information Professionals offers an accessible introduction to computational programming for information professionals. While best suited for readers with some prior programming familiarity, it provides a clear path to engaging with Python. The tone is approachable and free from typical programming manual clichΓ©s, encouraging readers to further explore coding's potential in library work. Recommended for graduate students, faculty, and professionals.

Book Hero reading reviews

Book Details

INFORMATION

ISBN: 9781538178256

Publisher: Bloomsbury Publishing Plc

Format: Paperback / softback

Date Published: 01 November 2023

Country: United States

Imprint: Rowman & Littlefield

Illustration: 9 b/w photos; 2 tables

Audience: Professional and scholarly

DIMENSIONS

Spine width: 12.0mm

Width: 151.0mm

Height: 228.0mm

Weight: 277g

Pages: 172

About the Author

Brady Lund, Ph.D., is an assistant professor of information science at the University of North Texas. He has published four books related to technology in libraries and educational institutions – including Casting Light on the Dark Web and Creating Accessible Online Instruction Using Universal Design Principles, both for Rowman and Littlefield Publishing – and nearly 100 articles, editorials, and opinion papers. His work often combines data analytics principles with library and information science research topics.
Daniel Agbaji is a Ph.D. student in information science at the University of North Texas, with a major in Data Science-Artificial Intelligence and Machine Learning. As an experienced researcher and software developer, he has written scholarly publications and book chapters with notable publishers. Daniel has published articles in the information science and library field. As a software developer, Daniel has written thousands of lines of code for fortune 500 companies which are not publicly available due to company policies.
Kossi Dodzi Bissadu is a Ph.D. student in the computer science at the University of North Texas. He currently works as a software engineer at Zenner USA where he leads various products, software, applications, and systems development projects. He is also a US Air Force veteran, very talented and dedicated professional who has more than ten-year professional record achievements, and demonstrated success leading, managing, and working in Technology and Sciences. Kossi has several industry certifications including certified blockchain developer, AWS certified cloud practitioner, and CompTIA Security+.
Haihua Chen, Ph.D., is an assistant professor of information science at the University of North Texas. He has more than ten years of experience in Python and five years of experience in teaching technical courses for information science and data science students using Python. Dr. Chen has published nearly 40 articles on natural language processing, machine learning, data quality, information retrieval, digital libraries, and applied data science. He is the editor of The Electronic Library and the leading guest editor of Frontiers in Big Data and Information Discovery & Delivery special issues. He is also serving as the reviewer/ PC member for more than 20 peer-review journals/ conferences in information science and computer science.

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